The prevalence of insomnia and the degree of impairment due to insomnia is greater than in the of young. The cause for insomnia in the elderly are various factors among the elderly is known to be high including medical, psychiatric, drug issues, circadian rhythm changes, sleep disorders, and psychosocial. So the careful evaluation to find the cause of insomnia is needed for the eldery. Treatment options for insomnia include behavior modification and pharmacotherapy. Outcome data from previous studies indicate that behavioral approaches produce reliable and durable therapeutic benefits, as evidenced by improved sleep efficiency and continuity and enhanced satisfaction with sleep patterns. Treatment methods such as stimulus control and sleep restriction, which target maladaptive sleep habits, are especially beneficial for older insomniacs, whereas relaxation-based interventions aimed at decreasing arousal, produce more limited effects. Cognitive and educational interventions are instrumental in altering age-related dysfunctional beliefs and attitudes about sleep. The choice of hypnotics is based on matching the nature of the insomnia to the hypnotic agent. The ideal agent has rapid onset, duration of action that lasts through the night but no residual daytime effects, and no adverse effects. The key for the healthcare professional is finding the appropriate treatment or treatment combination, including behavioral modification and pharmacotherapy. When hypnotics are indicated, the most appropriate short-acting agent should be considered.

In 2000, the number of people aged 65 and over increased to 3.37 million, accounting for 7.1% of the total population of South Korea. The elderly population will increase up to 19.3% in 2030. Sleep disordered breathing (SDB) seems to increase with age. More than 50-60% of old people complain of SDB-related signs and symptoms including awakening headache, excessive daytime sleepiness, fatigue, cognitive dysfunction, memory loss, personality changes, and depression. The influence of a mild degree of SDB upon the elderly is unclear, but moderate to severe SDB is well known to be associated with many diseases including hypertension, arrhythmia, myocardial infarction, stroke, dementia, and sudden death. Therefore, physicians should pay attention to elderly patients who complain of SDB related symptoms and signs that may not be normal signs of aging. Physicians need to become more sensitive to treat SDB in the elderly.

The change of sleep pattern is one of the most often altered normal physiological functions in elderly people. Besides normal change of sleep, insomnia and sleep apnea syndrome (SAS) are (one of) the main complaints. In addition, parasomnia is also frequent in this age group. Several parasomnias frequently found in the elderly are reviewed. Periodic limb movements in sleep (PLMS), restless legs syndrome (RLS), and REM sleep behavior disorder are the most frequent parasomnias in old age. Most parasomnias could be diagnosed by polysomnography, and be treated easily. Therefore, early and precise diagnosis and management for parasomnia in aging people are needed.

Objectives: Obstructive sleep apnea syndrome (OSA) is a moderately prevalent disorder. Even though much progress has been made in the diagnosis of this disorder, the cost-effectiveness of nocturnal polysomnography is undertermined and physicians and patients are still hesitant to undergo this procedure. The authors wanted to see the validity of chin press/tongue curl maneuver in estimating the severity of OSA which is easy to measure and was originally proposed by Simmons etc. by looking at the correlations between this score and the conventional respiratory disturbance indices. Methods: Forty-three sleep-related breathing disorder patients (28 OSA patients and 15 upper airway resistance syndrome (UARS) patients) who underwent investigation for posssible OSA were studied. Two conventional indices of OSA (apnea/hypopnea index (AHI) and oxygen saturation dip rate (SaO2 dips)), four other sleep variables (lowest SaO2, % of time with SaO2<90% (%SaO2 <90), % of sleep stage 1, mean length of SaO2 dips) and the score of Epworth sleepiness scale (ESS) were compared with the chin press score (CPS) which was newly revised by the author and ranges from 0 to 6. Results: The age of subjects was (range 14-76) and their average BMI was (range 19.65-37.64). There were no significant differences in age, sex and BMI except repiratory disturbance indices and ESS (p<0.05) between OSA and UARS group. Grouped median CPS of the all subjects was 4.14 (range 1-6). There was a remarkable relationship between CPS and diagnosis category (Likelihood Ratio test; =17.41, df=5, p=0.004) and measures of association (Somers' , t=4.83, p=0.000) indicated that CPS increased when the diagnosis changed from UARS to OSA. Spearman's rank correlations between CPS and SaO2 dips (R=0.83), between CPS and AHI (R=0.77) were good (p<0.001). Other variables except mean length of SaO2 dips showed good correlations with CPS as well (p<0.05). Regression analysis indicated that when CPS is 3 there is a provability of 0.35 to have AHI of less than 5. Conclusion: Chin press scores that can be measured easily is well correlation with the conventional sleep apnea indices. They may therefore provide a useful guide in diagnosing obstructive sleep apnea synrome.

Object: Diurnal variation is included in the diagnostic criteria of the major depressive disorder, melancholic specifier. But there has been controversy over whether diurnal variation is an unique depressive symptoms or a symptom related to a change of sleep patterns, or that of another mechanism, when the previous studies are reviewed. We investigated the existence of diurnal variation according to the subtype of depression and whether diurnal variation is charateristic of melancholic depression or not. We also compared sleep variables according to the existence of diurnal variation. Method: We examined diurnal variation, sleep patterns, severity of depression using the Visual Analogue Mood Scale, Pittsburgh Sleep Quality Index, and Hamilton Depression Rating Scale. Patients recorded their mood state on the Visual Analogue Mood Scale twice a day, morning and evening, for diurnal variation. We divided depressive patients into two groups,-diurnal variation group and nondiurnal variation group,-and compared the mood and sleep variables using SPSS. Results: The frequency of diurnal variation is not significantly different among the subtypes of depression. Significant differences between the diurnal variation group and the nondiurnal variation group existed in middle insomnia and sleep time (p<0.05). In melancholic type, al significant difference between the diurnal variation group and the nondiurnal variation group was noticed in PSQI total, sleep latency, sleep disturbances, daytime dysfunction as well as middle insomnia and sleep time (p<0.05). Conclusions: Diurnal variation existed in other types of depression as well as melancholic type. The results showed that diurnal variation was not a specific symptom of melancholic type, and existence of diurnal variation might be related to sleep patterns.

Background: Sleep disorders are prevalent in the general population and in medical practice. Three diagnostic classifications for sleep disorders have been developed recently: The International Classification of Sleep Disorders (ICSD), The Diagnostic and Statistical Manual, 4th edition (DSM-IV) and The International Classification of Diseases, 10th edition (ICD-10). Few data have yet been published regarding how the diagnostic systems are related to each other. To address these issues, we evaluated the frequency of sleep disorder diagnoses by DSM-IV and ICSD and compared the DSM-IV with the ICSD diagnoses. Method: Two interviewers assessed 284 inpatients who had been referred for sleep problems in general units of Anam Hospital, holding an unstructured clinical interview with each patient and assigning clinical diagnoses using ICSD and DSM-IV classifications. Results: The most frequent DSM-IV primary diagnoses were "insomnia related to another mental disorder (61.1% of cases)" and "delirium due to general medical condition (26.8%)". "Sleep disorder associated with neurologic disorder (38.4% of cases)" was the most frequent ICSD primary diagnosis, followed by "sleep disorder associated with mental disorder (33.1%)". In comparing the DSM-IV diagnoses with the ICSD diagnoses, sleep disorder unrelated with general medical condition or another mental disorder in DSM-IV categories corresponded with these in ICSD categories. But DSM-IV "primary insomnia" fell into two major categories of ICSD, "psychophysiologic insomni" and "inadequate sleep hygiene". Of 269 subjects, 62 diagnosed with DSM-IV sleep disorder related to general medical condition or another mental disorder disagreed with ICSD diagnoses, which were sleep disorders not associated with general medical condition or mental disorder, i. e., "inadequate sleep hygiene", "environmental sleep disorder", "adjustment sleep disorder" and "insufficient sleep disorder". Conclusion: In this study, we found not only a similar pattern between DSM-IV and ICSD diagnoses but also disagreements, which should not be overlooked by clinicians and resulted from various degrees of understanding of the pathophysiology of the sleep disorders among clinicians. Non-diagnosis or mis-diagnosis leas to inappropriate treatment, therefore the clinicians' understanding of the classification and pathophysiology of sleep disorders is important.

Objectives: The experience of traffic accident is a kind of the psychosocial stressors to person. The traffic accident-related patients may show the psychophysiologic hyperarousal. So we examined the differences of psychophysiologic response between patients with and without the memory of experienceing a traffic accident. Methods: Twenty-four traffic accident-related patients were divided into two groups according to ther memory of a traffic accident. In psychological assessment, levels of anxiety and depression were evaluated by State-Trait Anxiety Inventory, Beck's Depression Inventory, and Hamilton Rating Scales For Anxiety and Depression. Heart rate, electrodermal response (EDR), and electromyographic activity (EMG) were measured by biofeedback system, and systolic and diastolic blood pressure by automated vital sign monitor during baseline, task, and rest periods. We utilized script-driven imagery technique as a stressful task. The patients listened to the script describing their own traffic accident experience and were instructed to imagine the event during the task period. Statistically analytic data were obtained from the differences of psychological and psychophysiologic data between two groups. Results: The memory group did not show significantly higher EDR than the none memory group, but showed higher tendency during baseline, imagery, and rest periods. The memory group showed significantly lower EMG than the none memory group during rest period. However, there were no differences in other psychophysiologic reponses between the two groups. Conclusion: Our results showed that the memory group had higher tendency in autonomic arousal level such as electrodermal response than the none memory group. We suggest that physicians need to minimize repetitive imagery of traffic accident (reexperience), and decrease the autonomic hyperarousal in the treatment of traffic accident-related patients.

Objectives: An Increased level of psychophysiologic arousal and diminished physiologic flexibility would be observed in patients with panic disorder compared with a normal control group. We investigated the differences of psychophysiologic response between patients with panic disorder and normal control to examine this hypothesis. Methods: Ten Korean patients with panic disorder who met the diagnostic criteria of DSM-IV were compared with 10 normal healthy subjects. In psychological assessment, levels of anxiety and depression were evaluated by State-Trait Anxiety Inventory, Beck's Depression Inventory and Hamilton Rating Scale For Anxiety and Depression. Heart rate, respiration rate, electrodermal response, and electromyographic activity were measured by biofeedback system (J & J I-330 model) to determine psychophysiologic responses on autonomic nervous system. Stressful tasks included mental arithmetic, video game, hyperventilation, and talking about a stressful event. Psychophysiologic responses were measured according to the following procedures : baseline(3 min)-mental arithmetic (3 min)-rest (3 min)-video game (3 min)-rest (3 min)-hyperventilation (3 min)-rest (3 min)-talking about a stressful event (3 min). Results: The baseline level of anxiety and depression, electrodermal response (p=.017), electromyographic activity (p=.047) and heart rate (p=.049) of patients with panic disorder were significantly higher than those of the normal subject group. In electrodermal response, patient group had significantly higher startle response than the control group during hyperventilation (p=.001). Startle and recovery responses of heart rate in the patient group were significantly lower than responses in the control group during mental arithmetic (p=.007, p=.002). In electrodermal response of the patient group, startle response was significantly higher than recovery response during mental arithmetic (p=.000) and video game task (p=.021). Recovery response was significantly higher than startle response in respiratory response during hyperventilation. Conclusion: The results showed that patients with panic disorder had higher autonomic arousal than the control group, but the physiologic flexibility was variable. We suggest that it is helpful for treatment of panic disorder to decrease the level of autonomic arousal and to recover the physiologic flexibility in certain stressful event.

Objectives: This study examined the effect of mood and personality characteristics on psychophysiological responses measured by a biofeedback system in a normal population. Methods: Fifty healthy volunteers without any history of medical or psychiatric illnesses participated in this study. We measured the Spielberger trait anxiety inventory, Beck depression inventory, and Eysenck personality questionnaires in these subjects. Using the J & J biofeedback system, we also measured skin temperature, electrodermal response, forearm and frontal electromyography (EMG)s in 3 experimental conditions of baseline, stress, and recovery phases. Results: Trait anxiety did not show any significant correlation with psychophysiological responses except stress response in forearm EMG levels(r=0.282, p<0.05). Depressed mood was negatively correlated with forearm EMG levels in baseline (r=-0.299, p<0.05) and recovery phases(r=-0.314, p<0.05). Subjects with relatively high levels of depressed mood showed different stress and recovery responses in frontal EMG levels compared with those with relatively low levels of depressed mood (F=4.26, p<0.05). Extroverted subjects showed higher levels of forearm EMG than introverted ones in stress phase. Conclusion: Mood and personality characteristics in healthy subjects are closely related with psychophysiological responses measured by a biofeedback system. We suggest that mood and personality characteristics should be considered as important variables in analyzing abnormal psychophysiological responses in some psychiatric patients.

Independent Component Analysis (ICA) is a blind source separation method using unsupervised learning and mutual information theory created in the late eighties and developed in the nineties. It has already succeeded in separating eye movement artifacts from human scalp EEG recording. Several characteristic sleep waves such as sleep spindle, K-complex, and positive occipital sharp transient of sleep (POSTS) can be recorded during sleep EEG recording. They are used as stage determining factors of sleep staging and might be reflections of unknown neural sources during sleep. We applied the ICA method to sleep EEG for sleep waves separation. Eighteen channel scalp longitudinal bipolar montage was used for the EEG recording. With the sampling rate of 256Hz, digital EEG data were converted into 18 by n matrix which was used as a original data matrix X. Independent source matrix U (18 by n) was obtained by independent component analysis method (, where W is an 18 by 18 matrix obtained by ICA procedures). ICA was applied to the original EEG containing sleep spindle, K-complex, and POSTS. Among the 18 independent components, those containing characteristic shape of sleep waves could be identified. Each independent component was reconstructed into original montage by the product of inverse matrix of W (inv(W)) and U. The reconstructed EEG might be a separation of sleep waves without other components of original EEG matrix X. This result (might) demonstrates that characteristic sleep waves may be separated from original EEG of unknown mixed neural origins by the Independent Component Analysis (ICA) method.